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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM24357
Volume:
7 |
7 |
Jul 2023
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
The process of conducting interviews plays a pivotal role in human resource management, as it directly influences the selection of candidates and ultimately shapes the composition of an organization’s workforce. However, traditional interview methods are often subjective and prone to biases, leading to suboptimal decision-making. In recent years, the emergence of artificial intelligence (AI) technologies has provided new opportunities to revolutionize interview analysis and improve decision-making in the hiring process.This research paper explores the application of AI-enabled interview analysis in human resource management, aiming to unveil insights and enhance decision-making. The study focuses on three main areas: interview data collection, analysis, and decision-making support. AI technologies, including natural language processing (NLP) and machine learning algorithms, are leveraged to analyze interview transcripts, audio recordings, and other relevant data sources.By analyzing interview data using AI, this research uncovers hidden patterns, linguistic cues, and behavioural indicators that may be missed by human interviewers. These insights provide a deeper understanding of candidate suitability, skills, and competencies, enabling HR professionals to make more informed and objective decisions. Moreover, AI algorithms can be trained to identify biases and mitigate their impact, leading to fairer and more inclusive hiring practices. The research also investigates the potential challenges and ethical considerations associated with AI-enabled interview analysis. Concerns related to privacy, data security, algorithmic biases, and the role of human judgment in decision-making are examined, highlighting the need for responsible implementation and ongoing monitoring.To validate the effectiveness of AI-enabled interview analysis, a mixed-methods approach is employed, combining quantitative data analysis and qualitative feedback from HR professionals. The study presents empirical evidence demonstrating the benefits of AI technologies in improving decision-making accuracy, efficiency, and fairness. Key
KEYWORDS
Publication Date
4/6/2023
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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